Background Generalized Anxiety Disorder (GAD) is a common disorder in older adults which has been linked to hyperactivity of the Hypothalamic-Pituitary-Adrenal (HPA) axis in this age group. We examined whether treatment of GAD in older adults with a selective serotonin reuptake inhibitor (SSRI) corrects this HPA axis hyperactivity. Methods We examined adults aged 60 and above with GAD in a 12-week randomized controlled trial comparing the SSRI escitalopram to placebo. We collected salivary cortisol at six daily timepoints for two consecutive days to assess peak and total (area under the curve) cortisol, both at baseline and post-treatment. Results Compared with placebo-treated subjects, SSRI-treated subjects had a significantly greater reduction in both peak and total cortisol. This reduction in cortisol was limited to subjects with elevated (above the median) baseline cortisol, in whom SSRI-treated subjects showed substantially greater reduction in cortisol than did placebo-treated subjects. Reductions in cortisol were associated with improvements in anxiety. Additionally, genetic variability at the serotonin transporter promoter predicted cortisol changes. Conclusions SSRI treatment of GAD in older adults reduces HPA axis hyperactivity. Further research should determine whether these treatment-attributable changes are sustained and beneficial.

Context Generalized anxiety disorder (GAD) is one of the most common psychiatric disorders in older adults; however, few data exist to guide clinicians in efficacious and safe treatment. Selective serotonin reuptake inhibitors (SSRIs) are efficacious for younger adults with GAD, but benefits and risks may be different in older adults. Objective To examine the efficacy, safety, and tolerability of the SSRI escitalopram in older adults with GAD. Design, Setting, and Participants A randomized controlled trial in primary care practices and related specialty clinics in Pittsburgh, Pennsylvania, of 177 participants aged 60 years or older with a principal diagnosis of GAD randomized to receive either escitalopram or placebo and conducted between January 2005 and January 2008. Interventions Twelve weeks of 10 to 20 mg/d of escitalopram (n=85) or matching placebo (n=92). Main Outcome Measures Cumulative response defined by Clinical Global Impressions-Improvement score of much or very much improved; time to response; and anxiety and role functioning changes measured by the Clinical Global Impressions-Improvement scale, Hamilton Anxiety Rating Scale, Penn State Worry Questionnaire, Late-Life Function and Disability Instrument activity limitations subscale, and the role-emotional impairment and social function subscales of the Medical Outcome Survey 36-item Short Form. Results In the primary analytic strategy in which participants (n=33) were censored at the time of dropout, mean cumulative response rate for escitalopram was 69% (95% confidence interval [CI], 58%-80%) vs 51% (95% CI, 40%-62%) for placebo (P=.03). A conservative intention-to-treat analysis showed no difference in mean cumulative response rate between escitalopram and placebo (57%; 95% CI, 46%-67%; vs 45%; 95% CI, 35%-55%; P=.11). Participants treated with escitalopram showed greater improvement than with placebo in anxiety symptoms and role functioning (Clinical Global Impressions-Improvement scale: effect size, 0.93; 95% CI, 0.50-1.36; P<.001; Penn State Worry Questionnaire: 0.30; 95% CI, 0.23-0.48; P=.01; activity limitations: 0.32; 95% CI, 0.01-0.63; P=.04; and the role-emotional impairment and social function: 0.96; 95% CI, 0.03-1.90; P=.04). Adverse effects of escitalopram (P<.05 vs placebo) were fatigue or somnolence (35 patients [41.1%]), sleep disturbance (12 [14.1%]), and urinary symptoms (8 [9.4%]). Conclusions Older adults with GAD randomized to escitalopram had a higher cumulative response rate for improvement vs placebo over 12 weeks; however, response rates were not significantly different using an intention-to-treat analysis. Further study is required to assess efficacy and safety over longer treatment durations. Trial Registration clinicaltrials.gov Identifier: NCT00105586

In 2008, Blockchain was introduced to the world as the underlying technology of the Bitcoin system. After more than a decade of development, various Blockchain systems have been proposed by both academia and industry. This paper focuses on the consensus algorithm, which is one of the core technologies of Blockchain. In this paper, we propose a unified consensus algorithm process model that is suitable for Blockchains based on both the chain and directed acyclic graph (DAG) structure. Subsequently, we analyze various mainstream Blockchain consensus algorithms and classify them according to their design in different phases of the process model. Additionally, we present an evaluation framework of Blockchain consensus algorithms and then discuss the security design principles that enable resistance from different attacks. Finally, we provide some suggestions for selecting consensus algorithms in different Blockchain application scenarios.

Sharing trusted data among trusted stakeholders is very important to large-scale Internet of Things (IoT) applications. However, the entities and organizations involved in IoT naturally lack trusted relationships, which poses significant challenges to the above vision. Specifically, the first challenge is to ensure that the data in the physical world can be objectively and truly injected into the information world of IoT. The second is to ensure the credibility of the entities' identities in IoT. The third is to ensure the authenticity of data, the credibility of identity, and the reliable transmission of data when a third trusted party is unable to provide the expected trusted services. In view of the above challenges, this paper proposes a secure and lightweight triple-trusting architecture (SLTA), which fully uses a blockchain-related supporting technology. The architecture includes an oracle-based data collection mechanism, which ensures that the data collected from edge devices of IoT cannot be modified, and the distributed identity management mechanism, which enhances personal privacy, security, and control of digital identities. Furthermore, a series of innovative designs for applying the blockchain to special large-scale cooperation scenario in IoT are proposed, which is also a part of the key mechanisms of the SLTA. The innovative design includes a new software-defined blockchain structure model and a lightweight Byzantine fault-tolerant algorithm that provides credible support for decentralized data collection, identity management, and data transfer, as well as low-overhead sequential storage mechanism. KEYWORDSblockchain, Internet of Things, large-scale cooperation, trusted data sharing INTRODUCTIONWith the development of supporting technologies and the innovation of application modes, Internet of Things (IoT) has the potential to be one of the most popular paradigms in the era of Internet computing. In IoT 1 ecosystem, every entity equipped with identifying, sensing, networking, and processing capabilities has the ability to communicate with all other entities to accomplish some objective 2 through a multitype communication style. Although very large-scale IoT deployments remain a few years away, IoT is large scale 3 by nature. Medium-scale or even large-scale cooperation among smartThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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